No Distributed Quantum Advantage for Approximate Graph Coloring

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A4 Artikkeli konferenssijulkaisussa

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2024-06-10

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en

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10

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STOC 2024 - Proceedings of the 56th Annual ACM Symposium on Theory of Computing, pp. 1901-1910

Abstract

We give an almost complete characterization of the hardness of c-coloring χ-chromatic graphs with distributed algorithms, for a wide range of models of distributed computing. In particular, we show that these problems do not admit any distributed quantum advantage. To do that: We give a new distributed algorithm that finds a c-coloring in χ-chromatic graphs in Õ(n1/α) rounds, with α = ⌊c-1/χ - 1⌋. We prove that any distributed algorithm for this problem requires ω(n1/α) rounds. Our upper bound holds in the classical, deterministic LOCAL model, while the near-matching lower bound holds in the non-signaling model. This model, introduced by Arfaoui and Fraigniaud in 2014, captures all models of distributed graph algorithms that obey physical causality; this includes not only classical deterministic LOCAL and randomized LOCAL but also quantum-LOCAL, even with a pre-shared quantum state. We also show that similar arguments can be used to prove that, e.g., 3-coloring 2-dimensional grids or c-coloring trees remain hard problems even for the non-signaling model, and in particular do not admit any quantum advantage. Our lower-bound arguments are purely graph-theoretic at heart; no background on quantum information theory is needed to establish the proofs.

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Publisher Copyright: © 2024 Owner/Author.

Keywords

distributed computing, graph coloring, non-signaling model, quantum advantage

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Coiteux-Roy, X, D'Amore, F, Gajjala, R, Kuhn, F, Le Gall, F, Lievonen, H, Modanese, A, Renou, M O, Schmid, G & Suomela, J 2024, No Distributed Quantum Advantage for Approximate Graph Coloring . in B Mohar, I Shinkar & R O' Donnell (eds), STOC 2024 - Proceedings of the 56th Annual ACM Symposium on Theory of Computing . ACM, pp. 1901-1910, ACM Symposium on Theory of Computing, Vancouver, British Columbia, Canada, 24/06/2024 . https://doi.org/10.1145/3618260.3649679